Strategies & Skills Learning & Development
Home Support Service

Aging populations present a major challenge to most governments. Most analysts predict declining capacity of governments to provide adequate service for their senior citizens. With residential care costing way more than community services, governments policies are most likely encouraging more services to be provided in the community, and home support program will almost certainly grow.

Currently, most home support services are staffed by personal support workers (also called nursing aides or personal care workers in different jurisdictions) with minimal training. These workers are usually prepared to deal with physical care and assistance for daily living. Attention to psycho-social needs and wellbeing is minimal.

With shrinking government and public funding, we predict that there will be an increasing demand for home support service in the private market. For profit operators will bring new processes of competition to this service sector. This may help to improve quality and efficiency, but may also amplify the inequity in access to service. Public policy should focus on assisting the more vulnerable groups in obtaining adequate service.

The SSLD system enables practitioners to address the needs of seniors more comprehensively and more effectively. We have already developed an exciting repertoire of applications and tools, covering a wide range of challenging issues (e.g., dementia, depression, sexuality and intimacy, dysfunctional behavior, etc.). We believe the next generation of seniors service professionals will be equipped with a more multi-disciplinary knowledge base and skills set, and will provide a more comprehensive spectrum of services. SSLD is likely the best practice system to support such practice.

Leaders within the SSLD system are preparing for more active involvement in the training of the next generation of seniors service professionals in different parts of the world.

We are also exploring social entrepreneurial service delivery models to see if we can optimize service capacity within challenging fiscal contexts.